Machine Learning Platform Engineer

Apple Inc

Confirmed live yesterday High trust

Quick summary

Work type
On-site
Location
Seattle, WA
Salary
$175,000–$263,300 / yr
Posted
115 days ago
Freshness
Confirmed live yesterday

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $233k
This role $219k
$159k most similar roles pay here $320k

This role pays less than 61% of similar roles. Most pay $211,612–$254,750 — the shaded band above. At the midpoint, this role pays about $219k versus about $233k for comparable roles.

Based on 240 similar postings.

Employer

About Apple Inc

Apple Inc. is a multinational technology company known for designing and manufacturing consumer electronics, software, and online services, including the iPhone, Mac, iPad, and App Store. Industry: Consumer Electronics & Software

Apple Inc currently has 1984 open roles on FindRole.

Listed pay typically runs $175,000–$277,600 across 1590 roles with salary data.

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At a glance

TL;DR · Machine Learning Platform Engineer

Machine Learning Platform Engineer, Apple Services Engineering is a hands-on engineering role focused on building the evaluation platform for generative AI and agent systems. You will develop critical infrastructure including APIs, SDKs, orchestration components, and evaluation runners while productionizing ML research into reliable services. The role involves creating tools to evaluate non-deterministic AI systems at scale, ensuring high-quality developer experience through robust abstractions. Key technical requirements include proficiency in Python, FastAPI, Pydantic, and the modern Python ecosystem. You will also utilize AI coding tools and possess knowledge of the agentic LLM landscape, including tool use and multi-step reasoning. The work involves solving the complex problem of making non-deterministic model evaluations tractable for internal teams through production-grade software, while managing operational ownership across testing, CI/CD, containerization, and monitoring to ensure reliable system performance.

What you'll do

  • Develop and maintain evaluation platform components including APIs, SDKs, orchestration systems, and evaluation runners.
  • Convert research prototypes into reliable, production-ready services using clean Python code.
  • Build high-quality SDKs and abstractions to improve the developer experience for internal teams.
  • Manage the full lifecycle of production code by writing tests, setting up CI, and monitoring metrics.
  • Identify and resolve technical debt such as flaky tests, slow builds, and outdated documentation.
  • Balance rapid prototyping with rigorous engineering standards like design docs and careful rollouts.

What we're looking for

  • 4-8 years of software engineering experience building and shipping production services.
  • Proficiency in Python, including the FastAPI and Pydantic ecosystems.
  • Fluency with AI coding tools like Claude Code or similar agent-style workflows.
  • Familiarity with the agentic LLM landscape, including tool use, MCP servers, and multi-step reasoning.
  • Hands-on experience building evaluations for agents or using frameworks like Inspect, Braintrust, LangSmith, or Promptfoo.
  • Practical knowledge of LLMs in production, including prompt iteration, dataset curation, and statistical reasoning.
  • Solid engineering fundamentals in testing, CI/CD, Docker containerization, and observability.
  • Experience with developer platforms, job orchestration (Temporal, Airflow), or distributed compute (Ray, Dask).

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